Patricia M. Saco

Connectivity in dryland landscapes: shifting concepts of spatial interactions

Dryland ecosystems are often characterized by patchy vegetation and exposed soil. This structure enhances transport of soil resources and seeds through the landscape (primarily by wind and water, but also by animals), thus emphasizing the importance of connectivity – given its relation to the flow of these materials – as a component of dryland ecosystem function. We argue that, as with the fertile-islands conceptual model before it, the concept of connectivity explains many phenomena observed in drylands. Further, it serves as an organizing principle to understand dryland structure and function at scales from individual plants to entire landscapes. The concept of connectivity also helps to organize thinking about interactions among processes occurring at different scales, such as when processes at one scale are overridden by processes at another. In these cases, we suggest that state change occurs when fine-scale processes fail to adjust to new external conditions through resource use or redistribution at the finer scale. The connectivity framework has practical implications for land management, especially with respect to decision making concerning the scale and location of agricultural production or habitat restoration in the worlds drylands.

Coherent modes in multiscale variability of streamflow over the United States

Motivated by the need to understand large-scale hydrologic response, significant research has been directed toward the identification of coherent regions using characteristics of streamflow variability. Typically, these regions are delineated using principal component analysis on streamflow. This method does not account for differences in temporal scales of fluctuations embedded in the time series. To capture this, we use wavelet spectral analysis. Wavelet spectra from the specific streamflow series are obtained for outflow binned at 3°-length segments along the border of the conterminous United States. Rotated principal component analysis is performed on the wavelet spectra to obtain clusters of segments that exhibit similar distribution of variability across scales. Three physically distinct modes explain over 89% of the variability. Two of the modes identified are associated with high variability at seasonal scales, and the third is associated with high variability at small timescales. The runoff generation mechanisms underlying the observed modes of multiscale variability of various regions are also discussed. Each of these coherent modes of multiscale variability indicate the existence of regions with similar scales of fluctuations that are located geographically apart, as well as regions located geographically close with dissimilar scales of fluctuations.

Kinematic dispersion in stream networks. 2. Scale issues and self-similar network organization

[1] When the flow parameters, such as celerity and hydrodynamic dispersion coefficient, are allowed to vary spatially within a basin, three mechanisms, namely, geomorphologic, kinematic, and hydrodynamic dispersion, contribute to the variance of the instantaneous response function. The relative contributions of the three dispersion mechanisms as a function of scale, or Strahler order of the basin, are studied. This analysis is performed for two study basins, the Vermilion and the Mackinaw river basins, in central Illinois. Log linear trends for all the dispersion coefficients as a function of scale are observed. These trends can be cast in the form of Horton law type of relations. The asymptotic behavior of the dispersion coefficients of basins with self-similar network structure is consistent with the observations.

Causality and the entropy–complexity plane: Robustness and missing ordinal patterns

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the “causal” entropy–complexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martin, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigo, S. Zambrano, M.A.F. Sanjuan, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 2020–2029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r=4) to which we added correlated noise (colored noise with f−k Power Spectrum, 0≤k≤2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropy–complexity plane this goal can be achieved without additional computations.

Ecogeomorphic coevolution of semiarid hillslopes: Emergence of banded and striped vegetation patterns through interaction of biotic and abiotic processes

[1] Nonlinear interactions between physical and biological factors give rise to the emergence of remarkable landform‐vegetation patterns. Patterns of vegetation and resource redistribution are linked to productivity and carrying capacity of the land. As a consequence, growing concern over ecosystem resilience to perturbations that could lead to irreversible land degradation imposes a pressing need for understanding the processes, nonlinear interactions, and feedbacks, leading to the coevolution of these patterns. For arid and semiarid regions, causes for concern have increased at a rapid pace during the last few decades due to growing anthropic and climatic pressures that have resulted in the degradation of numerous areas worldwide. This paper aims at improving our understanding of the ecogeomorphic evolution of landscape patterns in semiarid areas with a sparse biomass cover through a modeling approach. A coupled vegetation‐pattern formation and landform evolution model is used to study the coevolution of vegetation and topography over centennial timescales. Results show that self‐organized vegetation patterns strongly depend on feedbacks with coevolving landforms. The resulting patterns depend on the erosion rate and mechanism (dominance of either fluvial or diffusive processes), which are affected by biotic factors. Moreover, results show that ecohydrologic processes leading to banded pattern formation, when coupled with landform processes, can also lead to completely different patterns (stripes of vegetation along drainage lines) that are equally common in semiarid areas. These findings reinforce the importance of analyzing the coevolution of landforms and vegetation to improve our understanding of the patterns and structures found in nature.

Assessing landscape structure and pattern fragmentation in semiarid ecosystems using patch-size distributions

Spatial vegetation patterns are recognized as sources of valuable information that can be used to infer the state and functionality of semiarid ecosystems, particularly in the context of both climate and land use change. Recent studies have suggested that the patch-size distribution of vegetation in drylands can be described using power-law metrics, and that these scale-free distributions deviate from power-law linearity with characteristic scale lengths under the effects of increasing aridity or human disturbance, providing an early sign of desertification. These findings have been questioned by several modeling approaches, which have identified the presence of characteristic scale lengths on the patch-size distribution of semiarid periodic landscapes. We analyze the relationship between fragmentation of vegetation patterns and their patch-size distributions in semiarid landscapes showing different degree of periodicity (i.e., banding). Our assessment is based on the study of vegetation patterns derived from remote sensing in a series of semiarid Australian Mulga shrublands subjected to different disturbance levels. We use the patch-size probability density and cumulative probability distribution functions from both nondirectional and downslope analyses of the vegetation patterns. Our results indicate that the shape of the patch-size distribution of vegetation changes with the methodology of analysis applied and specific landscape traits, breaking the universal applicability of the power-law metrics. Characteristic scale lengths are detected in (quasi) periodic banded ecosystems when the methodology of analysis accounts for critical landscape anisotropies, using downslope transects in the direction of flow paths. In addition, a common signal of fragmentation is observed: the largest vegetation patches become increasingly less abundant under the effects of disturbance. This effect also explains deviations from power-law behavior in disturbed vegetation which originally showed scale-free patterns. Overall, our results emphasize the complexity of structure assessment in dryland ecosystems, while recognizing the usefulness of the patch-size distribution of vegetation for monitoring semiarid ecosystems, especially through the cumulative probability distributions, which showed high sensitivity to fragmentation of the vegetation patterns. We suggest that preserving large vegetation patches is a critical task for the maintenance of the ecosystem structure and functionality.

Potential increase in coastal wetland vulnerability to sea-level rise suggested by considering hydrodynamic attenuation effects

The future of coastal wetlands and their ecological value depend on their capacity to adapt to the interacting effects of human impacts and sea-level rise. Even though extensive wetland loss due to submergence is a possible scenario, its magnitude is highly uncertain due to limited understanding of hydrodynamic and bio-geomorphic interactions over time. In particular, the effect of man-made drainage modifications on hydrodynamic attenuation and consequent wetland evolution is poorly understood. Predictions are further complicated by the presence of a number of vegetation types that change over time and also contribute to flow attenuation. Here, we show that flow attenuation affects wetland vegetation by modifying its wetting-drying regime and inundation depth, increasing its vulnerability to sea-level rise. Our simulations for an Australian subtropical wetland predict much faster wetland loss than commonly used models that do not consider flow attenuation.

The effect of landform variation on vegetation patterning and related sediment dynamics

Semi‐arid ecosystems are often spatially self‐organized in typical patterns of vegetation bands with high plant cover interspersed with bare soil areas, also known as ‘tiger bush’. In modelling studies, most often, straight planar slopes were used to analyse vegetation patterning. The effect of slope steepness has been investigated widely, and some studies investigated the effects of microtopography and hillslope orientation. However, at the larger catchment scale, the overall form of the landscape may affect vegetation patterning and these more complex landscapes are much more prevalent than straight slopes. Hence, our objective was to determine the effect of landform variation on vegetation patterning and sediment dynamics. We linked two well‐established models that simulate (a) plant growth, death and dispersal of vegetation, and (b) erosion and sedimentation dynamics. The model was tested on a straight planar hillslope and then applied to (i) a set of simple synthetic topographies with varying curvature and (ii) three more complex, real‐world landscapes of distinct morphology. Results show banded vegetation patterning on all synthetic topographies, always perpendicular to the slope gradient. Interestingly, we also found that movement of bands – a debated phenomenon – seems to be dependent on curvature. Vegetation banding was simulated on the slopes of the alluvial fan and along the valley slopes of the dissected and rolling landscapes. In all landscapes, local valleys developed a full vegetation cover induced by water concentration, which is consistent with observations worldwide. Finally, banded vegetation patterns were found to reduce erosion significantly as compared to other vegetation configurations.

A tale of two riffles: Using multidimensional, multifractional, time‐varying sediment transport to assess self‐maintenance in pool‐riffle sequences

Pool-riffle sequences play a central role in providing habitat diversity conditions both in terms of flow and substrate in gravel bed streams. Understanding their capacity to self-maintain has been the focus of research for many years, starting with the velocity reversal hypothesis. This hypothesis relied only on cross sectional averaged flow information, but its limited success prompted extensions of the hypothesis and alternative explanations for self-maintenance. Significant advances beyond the velocity reversal hypothesis have been achieved by incorporating more information either on flow or sediment transport characteristics. However, this has been done in a compartmentalised way, with studies either focusing on one or the other aspect. This work bridges the gap between these two aspects by using an approximate methodology that combines observed characteristic stage-dependent 3-D flow patterns with time-varying cross sectional information on bed shear stresses, sediment distribution and sediment bed changes during a one-year record of continuous discharges from a real stream. This methodology allows us to track the behaviour of different sediment size fractions along flow streamlines over time and identify self-maintenance conditions due to the combined effect of both flow multi-dimensionality and sediment transport. We apply this approximate methodology to two contiguous pools and riffles and demonstrate that, unexpectedly, they may rely on different mechanisms for self-maintenance due to differences in geometry and sediment size distribution. We also demonstrate that our methodology is potentially overarching and integrative of previous partial approaches based on flow multidimensionality or sediment transport, which tend to underestimate the occurrence of self-maintenance. This article is protected by copyright. All rights reserved.

The way forward : Can connectivity be useful to design better measuring and modelling schemes for water and sediment dynamics?

For many years, scientists have tried to understand, describe and quantify water and sediment fluxes, with associated substances like pollutants, at multiple scales. In the past two decades, a new concept called connectivity has been used by Earth Scientists as a means to describe and quantify the influences on the fluxes of water and sediment on different scales: aggregate, pedon, location on the slope, slope, watershed, and basin. A better understanding of connectivity can enhance our comprehension of landscape processes and provide a basis for the development of better measurement and modelling approaches, further leading to a better potential for implementing this concept as a management tool. This paper provides a short review of the State-of-the-Art of the connectivity concept, from which we conclude that scientists have been struggling to find a way to quantify connectivity so far. We adapt the knowledge of connectivity to better understand and quantify water and sediment transfers in catchment systems. First, we introduce a new approach to the concept of connectivity to study water and sediment transfers and the associated substances. In this approach water and sediment dynamics are divided in two parts: the system consists of phases and fluxes, each being separately measurable. This approach enables us to: i) better conceptualize our understanding of system dynamics at different timescales, including long timescales; ii) identify the main parameters driving system dynamics, and devise monitoring strategies which capture them; and, iii) build models with a holistic approach to simulate system dynamics without excessive complexity. Secondly, we discuss the role of system boundaries in designing measurement schemes and models. Natural systems have boundaries within which sediment connectivity varies between phases; in (semi-)arid regions these boundaries can be far apart in time due to extreme events. External disturbances (eg. climate change, changed land management) can change these boundaries. It is therefore important to consider the system state as a whole, including its boundaries and internal dynamics, when designing and implementing comprehensive monitoring and modelling approaches. Connectivity is a useful tool concept for scientists that must be expanded to stakeholder and policymakers.